cdisc-library-mcp-server

sdtm.byBiomedicalConcept

Retrieve SDTM dataset specializations that specialize a biomedical concept identified by its concept ID.

Instructions

List dataset specializations specializing a given Biomedical Concept (latest).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "conceptId": "<conceptId>"
    },
    "name": "sdtm.byBiomedicalConcept"
  }
}

Input Schema

Name	Required	Description	Default
`conceptId`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 12, 2026

TDQS

C2.8/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, description must disclose behavior. It mentions 'latest' version but lacks details on pagination, limits, error states, or what 'dataset specializations' entail (e.g., structure, scope). Minimal transparency for a list operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence is concise but contains redundancy ('specializations specializing') and could be clearer. Front-loads action, but word choice reduces clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given simple schema (1 param) and no output schema, description is adequate for basic listing but lacks context on what specializations are, how they relate to concepts, and how this differs from sibling tools. An agent would likely need additional context to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, so description must compensate. It adds 'Biomedical Concept' and 'latest' but does not explain conceptId format, source, or examples. Marginal value over schema, but incomplete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'List', resource 'dataset specializations', and context 'specializing a given Biomedical Concept (latest)'. It distinguishes from sibling tools like sdtm.list or sdtm.get by specifying 'specializations' and '(latest)', but doesn't fully differentiate from similar sibling sdtm.packages.getSpecialization.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives like sdtm.packages.getSpecialization or sdtm.domains. Agent must infer from context; missing explicit when-to-use or when-not-to-use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.